Computational assessment of methane-air reduced chemical kinetic mechanisms for soot production studies

Accurate predictions of minor chemical species and radicals are crucial for determining the production of pollutants such as soot. Reduced chemical kinetic mechanisms compromise their accuracy in favor of a lower computational cost. When using these reduced mechanisms then, it is important to assess both the accuracy of the results obtained, and the amount of computational time saved. This work describes such an assessment of seven methane-air reduced chemical kinetic mechanisms to be used for carrying out soot formation studies. The reduced mechanisms evaluated involve different numbers of chemical species and reaction steps. The assessment is carried out using partially stirred reactors, with and without in situ adaptive tabulation-based chemistry acceleration techniques, by comparing the results with detailed chemical kinetics baseline computations. In terms of accuracy, for equivalence ratios featuring significant amounts of soot (above ~1.5), and considering only those mechanisms that are readily used with the soot model utilized, the reduced mechanisms results show that major species are in general predicted reasonably well (~0–10 % discrepancies). Larger discrepancies between detailed and reduced mechanisms results (~0.2–16 %) are observed, however, when predicting minor species. The in situ adaptive tabulation technique used in this work leads to further reductions in the accuracy of the minor species predicted, i.e., to further increases in discrepancies (~0.1–7 %). Regarding the computational cost, the results show that savings of up to 57 % can be obtained when using the reduced mechanisms analyzed. The use of chemistry acceleration techniques results in further cost reductions ranging from 1 to 43 %. Additionally, discrepancies in the predictions of soot volume fraction of the order of 4–11 % are observed when using reduced mechanisms. The results obtained in this work emphasize overall the need of carefully selecting the reduced mechanism that is more suitable for a given application.